




import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin
class 		_A   (    _lowerCamelCase     ,  unittest.TestCase ):
  _UpperCamelCase  :     Dict					=     PhobertTokenizer
  _UpperCamelCase  :     Optional[int]					=     False






  def    __a     (    self						:      Any )						->       Optional[Any]:






       """simple docstring"""







       super().setUp()

       # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
       lowercase   :  str        =					['''T@@''', '''i''', '''I''', '''R@@''', '''r''', '''e@@''']
       lowercase   :  Tuple        =					dict(zip(_A ,		range(len(_A ) ) ) )
       lowercase   :  Union[str, Any]        =					['''#version: 0.2''', '''l à</w>''']
       lowercase   :  Dict        =					{'''unk_token''': '''<unk>'''}

       lowercase   :  Tuple        =					os.path.join(self.tmpdirname ,		VOCAB_FILES_NAMES['''vocab_file'''] )
       lowercase   :  Any        =					os.path.join(self.tmpdirname ,		VOCAB_FILES_NAMES['''merges_file'''] )

       with open(self.vocab_file ,		'''w''' ,		encoding='''utf-8''' ) as fp:
            for token in vocab_tokens:
                 fp.write(f"""{token} {vocab_tokens[token]}\n""" )
       with open(self.merges_file ,		'''w''' ,		encoding='''utf-8''' ) as fp:
            fp.write('''\n'''.join(_A ) )






  def    __a     (    self						:      int ,		**_A						:      Tuple )						->       List[str]:






       """simple docstring"""







       kwargs.update(self.special_tokens_map )
       return PhobertTokenizer.from_pretrained(self.tmpdirname ,		**_A )






  def    __a     (    self						:      Dict ,		_A						:      Union[str, Any] )						->       int:






       """simple docstring"""







       lowercase   :  Optional[int]        =					'''Tôi là VinAI Research'''
       lowercase   :  Optional[Any]        =					'''T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'''
       return input_text, output_text






  def    __a     (    self						:      Optional[int] )						->       int:






       """simple docstring"""







       lowercase   :  List[str]        =					PhobertTokenizer(self.vocab_file ,		self.merges_file ,		**self.special_tokens_map )
       lowercase   :  List[str]        =					'''Tôi là VinAI Research'''
       lowercase   :  str        =					'''T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'''.split()
       lowercase   :  Optional[Any]        =					tokenizer.tokenize(_A )
       print(_A )
       self.assertListEqual(_A ,		_A )

       lowercase   :  List[str]        =					tokens + [tokenizer.unk_token]

       lowercase   :  str        =					[4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_A ) ,		_A )



def 							UpperCamelCase_(					_A :Union[str, Any]	)->		List[str]:
			UpperCamelCase__       =							[0] * len(_A	)
			UpperCamelCase__       =							[]
			UpperCamelCase__       =							[]
			UpperCamelCase__       =							0

			for values in graph.values():
						for i in values:
									indegree[i] += 1

			for i in range(len(_A	)	):
						if indegree[i] == 0:
									queue.append(_A	)

			while queue:
						UpperCamelCase__       =							queue.pop(0	)
						cnt += 1
						topo.append(_A	)
						for x in graph[vertex]:
									indegree[x] -= 1
									if indegree[x] == 0:
												queue.append(_A	)

			if cnt != len(_A	):
						print("Cycle exists"	)
			else:
						print(_A	)


# Adjacency List of Graph
__UpperCamelCase     		=							{0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}







topological_sort(graph)


